HW4_2

Use ggplot to create bar plots of year and program.

class=read.table("classInterests.txt",header = TRUE)
p1=ggplot(class, aes(x=Year))+
  geom_bar(stat="Count", width=0.7, fill="steelblue")+
    labs(title="Barplot of Year")
p2=ggplot(class, aes(x=Program))+
  geom_bar(stat="Count", width=0.7, fill="steelblue")+
  labs(title="Barplot of Program")
p3=ggplot(class, aes(x=Year,fill=Program))+
  geom_bar()
ggplotly(p1)

ggplotly(p2)

ggplotly(p3)

Create plots of healthcare spending versus time color coded by states.

health_spending=read_csv("healthcare-spending.csv",skip=2)[1:52,]

## Parsed with column specification:
## cols(
##   .default = col_double(),
##   Location = col_character()
## )

## See spec(...) for full column specifications.

## Warning: 12 parsing failures.
## row col   expected    actual                      file
##  53  -- 25 columns 1 columns 'healthcare-spending.csv'
##  54  -- 25 columns 1 columns 'healthcare-spending.csv'
##  55  -- 25 columns 1 columns 'healthcare-spending.csv'
##  56  -- 25 columns 1 columns 'healthcare-spending.csv'
##  57  -- 25 columns 1 columns 'healthcare-spending.csv'
## ... ... .......... ......... .........................
## See problems(...) for more details.

health_spending=health_spending[!health_spending$Location=="United States",] 
health=gather(health_spending,key="year",value="spending",2:25)
health$year=extract_numeric(health$year)

## extract_numeric() is deprecated: please use readr::parse_number() instead

p= ggplot(health, aes(year, spending)) + 
  geom_line(aes(group = Location), colour = "grey50") + 
  geom_point(aes(colour = Location))
ggplotly(p)

Create a barplot of average health care spending by state.

d=matrix(as.numeric(as.matrix(health_spending)[,-1]),ncol=24)
avespend=data.frame(spend=apply(d,1,mean),location=health_spending$Location)
p=ggplot(avespend, aes(location, spend)) +
  geom_col(col="steelblue",fill="steelblue")+
    theme(axis.text.x = element_text(angle = 90, hjust = 1))
ggplotly(p)